Nasopharyngeal carcinoma risk prediction via salivary detection of host and Epstein-Barr virus genetic variants.
Nasopharyngeal carcinoma risk prediction via salivary detection of host and Epstein-Barr virus genetic variants.
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通过唾液检测宿主和 Epstein-Barr 病毒遗传变异来预测鼻咽癌风险
DOI：
10.18632/oncotarget.11144
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发表时间：
2017-11-10
期刊：
影响因子：
--
通讯作者：
Zeng YX
中科院分区：
文献类型：
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作者：
Cui Q;Feng FT;Xu M;Liu WS;Yao YY;Xie SH;Li XZ;Ye ZL;Feng QS;Chen LZ;Bei JX;Feng L;Huang QH;Jia WH;Cao SM;Chang ET;Ye W;Adami HO;Zeng YX
遗传易感性和EB病毒（Epstein-Barr virus，EBV）感染是鼻咽癌的重要病因。在这项研究中，在中国南方，鼻咽癌是地方病，在EBV编码的RPMS 1基因的单核苷酸多态性（SNP），（基因座155391：G > A [G155391 A]）和七个宿主SNP（rs1412829，rs28421666，rs2860580，rs2894207，rs31489，rs6774494，和rs 9510787）被证实与50例NPC病例和54例基于医院的对照组的咽喉洗涤样本和1925例NPC病例和1947例基于医院的对照组的血沉棕黄层样本中的NPC风险显著相关，分别我们建立了一种策略，在一个方便，非侵入性，成本效益高，并显示良好的依从性，使用唾液样本检测NPC相关的EBV和宿主SNP。通过将这些EBV和宿主遗传变异整合到基于人群的病例对照研究（包括1026例新发NPC病例和1148例对照）中的风险预测模型，对该策略的潜在效用进行了测试。受试者工作特征（ROC）曲线分析显示NPC风险预测模型的曲线下面积为0.74（95%CI：0.71 - 0.76）。NRI分析表明，EBV SNP的加入显著提高了模型的识别能力（NRI = 0.30，P < 0.001），提示EBV特征在鼻咽癌流行区的高危人群识别中具有重要的应用价值。综上所述，我们通过非侵入性唾液采样开发了一种有前途的NPC风险预测模型。该方法为鼻咽癌高危人群的筛查提供了一种简便、有效的方法。
Genetic susceptibility and Epstein-Barr virus (EBV) infection are important etiological factors in nasopharyngeal carcinoma (NPC). In this study, in southern China, where NPC is endemic, a single nucleotide polymorphism (SNP) in the EBV-encoded RPMS1 gene (locus 155391: G > A [G155391A]) and seven host SNPs (rs1412829, rs28421666, rs2860580, rs2894207, rs31489, rs6774494, and rs9510787) were confirmed to be significantly associated with NPC risk in 50 NPC cases versus 54 hospital-based controls with throat washing specimens and 1925 NPC cases versus 1947 hospital-based controls with buffy coat samples, respectively. We established a strategy to detect the NPC-associated EBV and host SNPs using saliva samples in a single test that is convenient, noninvasive, and cost-effective and displays good compliance. The potential utility of this strategy was tested by applying a risk prediction model integrating these EBV and host genetic variants to a population-based case-control study comprising 1026 incident NPC cases and 1148 controls. Receiver operating characteristic (ROC) curve analysis revealed an area under the curve of the NPC risk prediction model of 0.74 (95% CI: 0.71−0.76). Net reclassification improvement (NRI) analysis showed that inclusion of the EBV SNP significantly improved the discrimination ability of the model (NRI = 0.30, P < 0.001), suggesting the promising value of EBV characteristics for identifying high-risk NPC individuals in endemic areas. Taken together, we developed a promising NPC risk prediction model via noninvasive saliva sampling. This approach might serve as a convenient and effective method for screening the population with high-risk of NPC.